Sensitivity Analysis of a Transmission Interruption Model for the Soil-Transmitted Helminth Infections in Kenya

Area of Science:

• Mathematical modeling in public health
• Infectious disease epidemiology
• Parasitology

Background:

• Soil-transmitted helminths (STH) pose a significant global health burden, with an elimination target set for 2030.
• Effective STH control requires robust mathematical models for resource allocation and surveillance.
• Existing STH transmission models are complex, with numerous uncertain parameters, leading to potential counter-intuitive behaviors.

Purpose of the Study:

• To conduct a global sensitivity analysis (GSA) on a recently developed STH transmission model in Kenya.
• To identify and rank parameters influencing STH elimination outcomes.
• To quantify the impact of individual and combined parameters on model predictions.

Main Methods:

• Utilized the extended Fourier Amplitude Sensitivity Test (eFAST), a variance decomposition method, for GSA.
• Applied the eFAST method to an STH transmission model developed for Kenya.
• Computed sensitivity indices (SI) for each model parameter.

Main Results:

• The model's prediction of STH worm burden elimination was highly sensitive to specific parameter groups.
• Key influential parameters included water/sanitation improvements (ϕ), treatment rounds (τ), drug efficacy (h), adult treatment proportion (g), worm mortality (μ), and egg production dependence (γ).
• These parameters collectively demonstrated significant influence on STH elimination outcomes.

Conclusions:

• Targeting specific parameter groupings is essential for STH control programs aiming for community-wide elimination.
• Interventions focusing on water, sanitation, treatment coverage, drug efficacy, and worm mortality are critical for achieving the 2030 STH elimination goal.
• The identified key parameters provide a strategic roadmap for public health interventions in STH-endemic regions.